Semester of Graduation
Master of Science in Civil Engineering (MSCE)
Civil and Environmental Engineering Department
The scattering of light within a fluid, referred to as its turbidity, was investigated against the presence of suspended solids. A linear regression analysis was conduced against turbidity and the total count, combined surface area, and combined volume of the suspended particles for various surface water sources (lakes, rivers, indoor aquaculture systems). It was found that the total combined surface area of suspended particles had the best linear correlation to turbidity, with an adjusted R2 of 81.79%. This correlation was integrated with a current theoretical model for predicting solids removal across a granular bed to yield an Integrated Turbidity Removal Model. This model was then calibrated against three different media types at three different flux rates, and proved to be a reasonably accurate at predicting the effectiveness of the granular bed on removing turbidity. A sensitivity analysis was conducted using the newly calibrated Integrated Turbidity Removal Model and it found that the variables that impact the effectiveness of the bed to remove turbidity the most are the particle density, filtration rate (flux rate), and media size.
Louque, Matthew, "Low-Density Static Granular Media Filter Bed Turbidity Removal Model" (2019). LSU Master's Theses. 4843.